__author__ = 'smathias'
import os
import pandas
import solarpy.py2solar.parse as parse
import solarpy.utils.paths as paths
from make_asym_jobs import structures
path = paths.pj(paths.OUTPUTS_DIR, 'asymmetries_mpi')
data = []
for structure in structures:
dic = {'name': structure}
for x in ['Bilateral_', 'Left_', 'Right_', 'Asym_', 'Abs_Asym_']:
_f = x + structure + '.sub'
f = paths.pj(path, [f for f in os.listdir(path) if _f == f[:len(_f)]][0])
_dic = {x + k: v for k, v in parse.uni_polyg(f).iteritems()}
dic.update(_dic)
_f = 'rhog_' + structure + '.sub'
f = paths.pj(path, [f for f in os.listdir(path) if _f in f][0])
_dic = parse.biv_polyg(f)
dic.update(_dic)
data.append(dic)
df = pandas.DataFrame(data)
df.to_csv('results.csv')
"""
Grab the sats.
"""
__author__ = 'smathias'
import os
import pandas
import solarpy.py2solar.parse as parse
import solarpy.utils.paths as paths
outputs_dir = paths.pj(paths.OUTPUTS_DIR, 'braincog')
output_files = os.listdir(outputs_dir)
entries = {}
print len(output_files)
for f in output_files:
dic = parse.uni_polyg(paths.pj(outputs_dir, f))
entries[f.split('.')[0]] = dic
df = pandas.DataFrame(entries).T
df = df.drop(['f', 'trait', 'n', 'se'], axis=1)
df.to_csv('h2rs.csv')
